Literature DB >> 27170908

Integration of New Technology for Research in the Emergency Department: Feasibility of Deploying a Robotic Assessment Tool for Mild Traumatic Brain Injury Evaluation.

Vignesh Subbian, Jonathan J Ratcliff, Jason M Meunier, Joseph J Korfhagen, Fred R Beyette, George J Shaw.   

Abstract

UNLABELLED: The objective of this paper is to demonstrate the effective deployment of a robotic assessment tool for the evaluation of mild traumatic brain injury (mTBI) patients in a busy, resource-constrained, urban emergency department (ED).
METHODS: Functional integration of new robotic technology for research in the ED presented several obstacles that required a multidisciplinary approach, including participation from electrical and computer engineers, emergency medicine clinicians, and clinical operations staff of the hospital. Our team addressed many challenges in deployment of this advanced technology including: 1) adapting the investigational device for the unique clinical environment; 2) acquisition and maintenance of appropriate testing space for point-of-care assessment; and 3) dedicated technical support and upkeep of the device. Upon successful placement of the robotic device in the ED, the clinical study required screening of all patients presenting to the ED with complaints of head injury. Eligible patients were enrolled and tested using a robot-assisted test battery. Three weeks after the injury, patients were contacted to complete follow-up assessments.
RESULTS: Adapting the existing technology to meet anticipated physical constraints of the ED was performed by engineering a mobile platform. Due to the large footprint of the device, it was frequently moved before ultimately being fully integrated into the ED. Over 14 months, 1423 patients were screened. Twenty-eight patients could not be enrolled because the device was unavailable due to operations limitations. Technical problems with the device resulted in failure to include 20 patients. A total of 66 mTBI patients were enrolled and 42 of them completed both robot-assisted testing and follow-up assessment. Successful completion of screening and enrollment demonstrated that the challenges associated with integration of investigational devices into the ED can be effectively addressed through a collaborative patient-oriented research model.
CONCLUSION: Effective deployment and use of new robotic technology for research in an urban academic ED required significant planning, coordination, and collaboration with key personnel from multiple disciplines. Clinical Impact: A pilot clinical study on mTBI patients using the robotic device provided useful data without disrupting the ED workflow. Integration of this technology into the ED serves as an important step toward pursing active clinical research in an acute care setting.

Entities:  

Keywords:  Clinical engineering; emergency department; neurological assessment; technology integration

Year:  2015        PMID: 27170908      PMCID: PMC4848098          DOI: 10.1109/JTEHM.2015.2424224

Source DB:  PubMed          Journal:  IEEE J Transl Eng Health Med        ISSN: 2168-2372            Impact factor:   3.316


  20 in total

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Authors:  Alisa D Gean; Nancy J Fischbein
Journal:  Neuroimaging Clin N Am       Date:  2010-11       Impact factor: 2.264

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Authors:  James H Nichols
Journal:  Clin Lab Med       Date:  2007-12       Impact factor: 1.935

Review 3.  Potential of robots as next-generation technology for clinical assessment of neurological disorders and upper-limb therapy.

Authors:  Stephen H Scott; Sean P Dukelow
Journal:  J Rehabil Res Dev       Date:  2011

4.  The Rivermead Post Concussion Symptoms Questionnaire: a measure of symptoms commonly experienced after head injury and its reliability.

Authors:  N S King; S Crawford; F J Wenden; N E Moss; D T Wade
Journal:  J Neurol       Date:  1995-09       Impact factor: 4.849

5.  Symptomatology and functional outcome in mild traumatic brain injury: results from the prospective TRACK-TBI study.

Authors:  Paul McMahon; Allison Hricik; John K Yue; Ava M Puccio; Tomoo Inoue; Hester F Lingsma; Sue R Beers; Wayne A Gordon; Alex B Valadka; Geoffrey T Manley; David O Okonkwo
Journal:  J Neurotrauma       Date:  2013-10-31       Impact factor: 5.269

6.  Quantitative assessment of post-concussion syndrome following mild traumatic brain injury using robotic technology.

Authors:  Vignesh Subbian; Jason M Meunier; Joseph J Korfhagen; Jonathan J Ratcliff; George J Shaw; Fred R Beyette
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2014

7.  Predicting postconcussion syndrome after mild traumatic brain injury in children and adolescents who present to the emergency department.

Authors:  Lynn Babcock; Terri Byczkowski; Shari L Wade; Mona Ho; Sohug Mookerjee; Jeffrey J Bazarian
Journal:  JAMA Pediatr       Date:  2013-02       Impact factor: 16.193

8.  Quantitative assessment of limb position sense following stroke.

Authors:  Sean P Dukelow; Troy M Herter; Kimberly D Moore; Mary Jo Demers; Janice I Glasgow; Stephen D Bagg; Kathleen E Norman; Stephen H Scott
Journal:  Neurorehabil Neural Repair       Date:  2009-09-30       Impact factor: 3.919

9.  Outcome prediction in mild traumatic brain injury: age and clinical variables are stronger predictors than CT abnormalities.

Authors:  Bram Jacobs; Tjemme Beems; Maja Stulemeijer; Arie B van Vugt; Ton M van der Vliet; George F Borm; Pieter E Vos
Journal:  J Neurotrauma       Date:  2010-04       Impact factor: 5.269

10.  Understanding practice: the factors that influence management of mild traumatic brain injury in the emergency department--a qualitative study using the Theoretical Domains Framework.

Authors:  Emma J Tavender; Marije Bosch; Russell L Gruen; Sally E Green; Jonathan Knott; Jill J Francis; Susan Michie; Denise A O'Connor
Journal:  Implement Sci       Date:  2014-01-13       Impact factor: 7.327

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Journal:  IEEE J Transl Eng Health Med       Date:  2017-05-02       Impact factor: 3.316

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Authors:  Cameron S Mang; Tara A Whitten; Madeline S Cosh; Sean P Dukelow; Brian W Benson
Journal:  J Athl Train       Date:  2020-11-01       Impact factor: 2.860

3.  Test-retest reliability of the KINARM end-point robot for assessment of sensory, motor and neurocognitive function in young adult athletes.

Authors:  Cameron S Mang; Tara A Whitten; Madeline S Cosh; Stephen H Scott; J Preston Wiley; Chantel T Debert; Sean P Dukelow; Brian W Benson
Journal:  PLoS One       Date:  2018-04-24       Impact factor: 3.240

4.  Physiological Vibration Acceleration (Phybrata) Sensor Assessment of Multi-System Physiological Impairments and Sensory Reweighting Following Concussion.

Authors:  John D Ralston; Ashutosh Raina; Brian W Benson; Ryan M Peters; Joshua M Roper; Andreas B Ralston
Journal:  Med Devices (Auckl)       Date:  2020-12-08
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